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Estimating the Parameters of Azzalini Model by Bayesian Approach Under Symmetric and Asymmetric Loss Functions
Volume 16, Issue 3 (2018), pp. 567–592
Janardan Mahanta   Soma Chowdhury Biswas   Manindra Kumar Roy  

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https://doi.org/10.6339/JDS.201807_16(3).0007
Pub. online: 4 August 2022      Type: Research Article      Open accessOpen Access

Published
4 August 2022

Abstract

Abstract:This paper has been proposed to estimate the parameters of Markov based logistic model by Bayesian approach for analyzing longitudinal binary data. In Bayesian estimation selection of appropriate loss function and prior density are most important ingredient. Symmetric and asymmetric loss functions have been used for estimating parameters of two state Markov model and better performance has been observed by Bayesian estimate under squared error loss function.

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Keywords
Modified linear exponential Markov model

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  • Online ISSN: 1683-8602
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